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On the effects of node duplication and connection-oriented constructivism in neural XCSF

Gerard David Howard, Larry Bull
2008 Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation - GECCO '08  
This paper presents the use of constructivism-inspired mechanisms within a neural learning classifier system which exploits parameter self-adaptation as an approach to realize such behavior.  ...  Various network growth/regression mechanisms are implemented and their performances compared. The system uses a rule structure in which each is represented by an artificial neural network.  ...  In particular, we explore the success of extensions to the XCSF-based neural LCS, N-XCSF [11] , including node duplication, and a connection-oriented neural constructivism scheme, on a real-valued version  ... 
doi:10.1145/1388969.1389010 dblp:conf/gecco/HowardB08 fatcat:2uhdczusnbcjridambe7fcmgqi

Knowledge Representation in Learning Classifier Systems: A Review [article]

Farzaneh Shoeleh, Mahshid Majd, Ali Hamzeh, Sattar Hashemi
2015 arXiv   pre-print
The current work is an attempt to find a comprehensive and yet elaborate view into the existing knowledge representation techniques in LCS domain in general and XCS in specific.  ...  Recently, knowledge representation component has received great deal of attention within data mining communities due to its impacts on rule based systems in terms of efficiency and efficacy.  ...  The first connection of each input node is assigned to the corresponding locus of such input and other connections are set at random.  ... 
arXiv:1506.04002v1 fatcat:mpwk7ga3azbh5akoe3coaydp2q